UMSL Presentation
February 19, 2002
by:
Allen Paschke
(636) 405-0375
AJPaschke@aol.com
Integrated Logistics
Introduction to Insight
INSIGHT – Who We Are
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INSIGHT Started 1978
Extensive Supply Chain Design Experience
Professional Staff
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Various Honors and Awards
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CLM Distinguished Service Award
US Offices
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35 employees
Average tenure – over 17 years experience
Manassas, VA
Bend, OR
Emphasis on Research and Application
Supply Chain Software
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Supply Chain Design
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Tactical Modules
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SAILS
Transportation Planning – SHIPCONS II
International Trade – GSCM
Components
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Labor Scheduling, Master Production Planning,
Supply Planning, Service Resource Scheduling,
Dynamic Sourcing
Oil/Chemical/Medical
Food & Beverage/CPG
Abbott Laboratories
BP Amoco
Allegiance Healthcare
Cytec
Bristol-Myers Squibb
BASF
Pennzoil
PPG Industries
Ipiranga
Exxon Mobil (5 continents)
Exxon Mobil Chemical
Pfizer
Johnson & Johnson
Ross Laboratories
Monsanto (Flexsys NV)
IMC Agrico
McKesson HBOC
Solutia
Manufacturing/Parts Distribution
Ferguson Enterprises
Toyota Motor Sales
Toyota Parts
Goodyear Tire & Rubber Co
Case New Holland
Case Parts
Georgia Pacific
Sears
Ingram Books
Purolator
Potlatch
R.R. Donnelly
Toyo Engineering
GE Service Parts
GE Appliances
Technology
Compaq
IBM Global Services
Motorola
Ameriserv, Inc.
CSI
Frito Lay
Frito Lay Int’l
Colgate
Perrier
Dr. Pepper - 7Up
Procter & Gamble
ConAgra
Walker Gillette
Borden Foods
Mars
Pepsi-Cola
Pepsi-Cola Int’l
Pepsi Bottling
Ralston Purina
Avon Products
Nabisco
Clorox
Unilever
Kraft Foods
Dean Foods
Consultants/3PL’s
Accenture
KPMG Peat Marwick
Frigoscandia
Norfolk Southern
Pricewaterhouse Coopers
Defense Logistics Agency
APL
CSC
Mark VII
SABRE
Integrated Logistics
The Concept
CLM Definition 1995
Logistics is the process of planning,
implementing,and controlling the efficient,
effective flow and storage of goods, services, and
related information from point of origin to point of
consumption for the purpose of conforming to
customer requirements.
Integrated Logistics System Design Model
Potential Network Schematic
Raw Materials
Finished Products
FW1
CZ1
P1
FW2
CZ2
FW3
CZ3
PW1
P2
S1
PW2
P3
S2
CZ4
FW4
CZ5
PW3
FW5
CZ6
Inbound
Replenishment
Transfer
Outbound
Evolution of Thought and Practice
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Individual Dispersed Functions
Conflicting
objectives
within the
logistics
function
TRANSPORTATION
WAREHOUSING
INVENTORY
Evolution of Thought and Practice
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Individual Dispersed Functions
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Integration Within Distribution
Conflicting
objectives
within the
firm
Manufacturing
Logistics
Purchasing
Evolution of Thought and Practice
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Individual Dispersed Functions
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Integration Within Distribution
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Integration Across Corporate Functions
Evolution of Thought and Practice
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Individual Dispersed Functions
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Integration Within Distribution
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Integration Across Corporate Functions
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Integration Across Supply Chain,
finding win-wins with Suppliers and
Customers
Network Redesign Business Questions
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How many distribution centers (D.C.s) should we have?
Where should the D.C.s be located?
Which customers should be served by each D.C.?
How do you best balance inventories against customer
service needs and distribution costs?
Should we contract for warehousing services or operate
our own D.C.s?
Should pool points be used and where should they be
located?
What do you gain by plant direct shipping?
Should all D.C.s carry all products or should they be
specialized by product line?
Where should my plants be located?
Which product lines should be produced at each plant and
how much?
Which suppliers should be used?
Do you need a Network Redesign?
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You would like answers to some of the 11
“business questions”
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You have never redesigned your network(s) or it
has been many years since the last redesign was
completed
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Multiple divisions exist within the parent
company and you are not leveraging
Warehousing and/or Transportation.
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You are acquiring a company
Integrated Logistics
Process to Redesign Supply Chains
Introduction
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Redesigning a Supply Chain is a PROCESS
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The SAILS software is a TOOL used in this process
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When you’re redesigning a Supply Chain, a good
process is beneficial.
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This is the process that I’ve used many times, with
good results, to redesign Supply Chains.
The Process
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Establish Project Management
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Define Objectives and Scope
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Design Model
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Data Collection
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Model Validation
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Optimization
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“What If” and Sensitivity Analysis
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Recommendation
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Implementation
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Post-Implementation Review
Project Management
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Establish Project Sponsor
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Best experiences with CFO or CEO
Why has the project been initiated?
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What is the “compelling event”?
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What needs improving?
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Too much Inventory
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Customer Service lead times need tightened
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Logistics Costs too high
Project Management
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Executive ("Steering") Committee required?
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Establish cross-functional team (MIS, Logistics,
Sales, Manufacturing, Customer Service,
Purchasing, R&D, Finance, etc.), usually VP or
Director level:
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Break down organization "silos"
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Create a better solution
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Improve the probability that the solution will be
accepted by the entire organization
Meet every 6 - 8 weeks
Project Management
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Establish full-time Project Manager
Establish Working Committee
• Establish team, usually Manager level, with "hands
on" responsibility to spend 25 to 50 percent working
on this project
• Meet "formally" every 2 - 3 weeks
Utilize Steering Committee to create “Task Forces”:
• Customer Service
• Product Compatibility and R&D Requirements
(temperature, etc.)
• Inventory Carrying Cost Methodology
• Accounting Issues, such as Fixed vs. Variable
Warehousing Costs
Objectives and Scope
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Objectives (and Goals)
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Why has the project been initiated? (What needs
improving)?
What business question(s) do you need answered?
Define as many "What If" and Sensitivity Analysis
questions to be answered, as possible
STAY STRATEGIC
Scope
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Which Business Units included?
Due to product incompatibilities, do multiple Supply
Chains need to be designed? How many?
Outbound (and Inbound(?))?
U.S. (and Canada(?) and Mexico(?))?
Include/exclude import/export (port)?
Model Design
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To design the model correctly, the objectives, the
scope, and as many "What If" and Sensitivity Analysis
questions, as possible, should be defined. Failure to
do this, will increase the risk that the model will not be
designed correctly, requiring extensive efforts to
redesign the model later in the project.
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First step, sketch the current flows of the existing
supply chain(s), defining all the “links”. Discuss what
future flows should be allowed
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How many supply chains need to be designed?
Sketch them.
Model Design
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For each supply chain (model):
• How many echelons?
• Current and candidate D.C.s, cross-docks, etc.
• How do you ship products (Small Package, LTL, TL,
Pool, Pick-up, Rail, etc.)
• D.C., cross-dock, etc. missions
• Customer Service guidelines, current, proposed
and “what if”
• Etc., etc.
Roles and responsibilities of each member of the
Working Committee. Assign tasks and due dates.
Data Collection
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Collect:
• Network Description
- Locations (Customers, D.C.s, Plants, Suppliers)
• Transportation Costs
- Inbound, Replenishment, Transfer, Outbound
• Demand Data
- Every Line Item from Every Order for a year
• Facility Data (Suppliers, Plant and D.C.)
- Fixed & Variable Costs
- Capacities
• Eligibility
- D.C.s
- Product Master with Production Source(s) Identified
- Suppliers
VERIFY all data to ensure that it is valid
Model Validation
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First, replicate flows (volumes)
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MY GOAL --- 99.75+% accurate
Second, replicate costs. (This is an iterative process,
until the variance between actual and the model reach
an acceptable level).
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MY GOAL:
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Nationally, within 1 to 2 percent of “unexplained”
variance.
By facility, within 5 percent of “unexplained”
variance.
Model Validation
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(If the “unexplained” variance is at the 5 - 10 percent
range, no confidence exists when an optimization run
shows a 10 percent cost reduction. It is not until the
“unexplained” variance is in the 1 to 2 percent range
that an optimization run showing a 10 percent cost
reduction can be believed).
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Develop spreadsheet, starting with the model
(validation) costs, adjusting for known (“explained”)
variances, and comparing to actual costs
Model Validation
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“Explained” Variances (examples):
• Transportation Costs
- Returns/Product Recall
- Damaged
- Accessorial (Fuel, Delay, Lumpers, etc.)
- Expedited Transportation
- Accounting Anomalies
• Warehousing Costs
- Different Inventory Turns
- Overflow Warehousing
- Accessorial (Special Services, extra shifts,
overtime, etc).
- Accounting Anomalies
• Plant Costs
Optimization
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Optimize the Supply Chain, meeting the customer
service Requirements.
(This should occur very quickly, a majority of
the analysis should be "What If" and Sensitivity
analysis).
“What If” and Sensitivity Analysis
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Most common Analysis:
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Sensitivity Analysis:
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Distribution cost vs. number of D.C.s
Distribution cost vs. Customer Service
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Cost for improved service
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As service is improved, are current D.C.s
still being utilized
“What If” and Sensitivity Analysis
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Most Common Analysis (continued)
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- Impact of inflation (D.C. vs transportation costs)
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Growth Analysis (can handle forecasted growth)
Impact of plant capacity expansion (new plants)
Impact of new product introduction
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Which plant
– 1 vs. 2 plants
D.C. capacity expansion
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Alternative echelon networks
– Plant direct
– Cross-Docks / UPS Zone Skipping
Implementation priority analysis
Recommendation
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A recommendation should be made, including:
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Supply Chain ("flow" and costs), AS IS
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Supply Chain ("flow" and costs), TO BE
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Expected benefits
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What was analyzed but didn't produce benefits
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Implementation plan, including
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Priorities
- Technology
Organizational impact
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Implementation
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Additional time should be planned for further
"What If" and Sensitivity Analysis to assist the
implementation team.
(For example, the model recommends a D.C.
in Omaha. The implementation team can not find
the space in Omaha at a reasonable price. What
is the additional transportation cost if the D.C.
were in Kansas City or Des Moines)?
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Now is the time to support the implementation
with tactical analysis.
Post-Implementation Review
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I’m a strong believer that 6 to 12 months after the
implementation, the project should be evaluated
and the actual benefits quantified.
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Most of my recommendations have reduced the
number of D.C.s, so more volume was going
through fewer locations. Due to increased
leverage (transportation and warehousing), the
actual benefits usually exceed what the software
predicted.
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All projects 5 to 15 percent Logistics savings
Majority in 8 to 12 percent range
Integrated Logistics
The Optimizer
Too often users don’t ask enough questions about
what the solver does and how. They seem to
assume that if a program can make pretty pictures,
it must also be able to get good answers.
In short, THEY BUY THE PICTURES,
NOT THE SOLUTIONS!
SAMPLE PROBLEM
DC1
PLANT 1
Capacity: 
CZ2
100,000
CZ3
50,000
3
5
4
DC2
4
2
Capacity: 60,000
50,000
3
0
PLANT 2
CZ1
2
0
1
HEURISTIC SOLUTION 1
“LEAST OUTBOUND COST”
DC1
PLANT 1
CZ1
50,000
CZ2
100,000
CZ3
50,000
3
0
3
140,000
PLANT 2
5
4
DC2
4
2
2
0
60,000
1
Inbound cost
Outbound cost
Total
$820,000
$150,000
$970,000
HEURISTIC SOLUTION 2
“LEAST TOTAL FLOW COST”
DC1
PLANT 1
50,000
CZ2
100,000
CZ3
50,000
3
0
3
50,000
5
PLANT 2
CZ1
4
DC2
90,000
4
2
2
0
60,000
1
Inbound cost
Outbound cost
Total
$570,000
$200,000
$770,000
The key to good analysis is the
range and quality of alternatives
generated for evaluation.
Solver Technology: Heuristics
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Characteristics
• common sense consideration of limited
alternatives
• not guaranteed to find best solution
• solution dependent upon quality of decision rules
• run-to-run comparisons unreliable
Applications
– crew scheduling
– vehicle routing
– shipment planning
Solver Technology: Simulation
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Characteristics
• imitates sequence of events/conditions over time
• no attempt to find best solution
• limited to process evaluation
• difficult to validate
• expensive to develop, maintain, and run
• run-to-run comparisons very difficult
Applications
– queuing problems
– inventory control
– plant/DC operations
OPTIMIZATION generates and considers
all alternatives in a given scenario -with heuristics and expert systems alone,
many alternatives are never envisioned,
much less evaluated!
Solver Technology: Optimization
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Characteristics
• evaluates all possible alternatives
• guaranteed to find best solution
• run-to-run comparisons reliable
• not widely available
Applications
– network design
– production planning
– cash flow planning
SOLVER TECHNOLOGY
*SAILS is TRUE OPTIMIZATION
USING MIXED INTEGER LINEAR PROGRAMMING
(*RESEARCH PUBLISHED IN REFEREED ACADEMIC JOURNALS)
OPTIMAL SOLUTION
“TRUE LEAST COST”
DC1
PLANT 1
CZ1
3
0
3
140,000
5
PLANT 2
40,000
4
DC2
4
50,000
2
CZ2
2
100,000
60,000
0
60,000
1
Inbound cost
Outbound cost
Total
$120,000
$470,000
$590,000
CZ3
50,000
Good models are like bright lights
focused on dark corners.
Conventional wisdom is frequently
wrong -- Management Science has
shown this time and time again.
Integrated Logistics
SAILS Model
Multiple Stages of Manufacture
STAGE 1
STAGE 2
Line 1
Line 1
Raw
materials
Line 2
Line 2
Finished
in
Line 3
Line 3
products
out
Raw
materials
Intermediate
products
Finished
products
Important Model Features
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Multiple stages of manufacture (conversions)
Multiple processing lines per stage
N-echelons of distribution centers
Multiple cost functions per facility
Sole source option
Facility status: fix/float options
Multi-Time Periods
PRODUCT AGGREGATION
Stock Codes
Product Groups
TR 968-14
TR 472-10
TR 784-16
1. Tires
TR 968-14
TR 472-10
TR 784-16
EL 497-23
2. Electronics
TR 968-14
TR 472-10
TR 784-16
CQ 491-79
3. Mechanical
DEMAND DATA: TARGET
Customer
zones 1
2
3
4
5
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L
Product Groups
1
2
3
4
X
5.......I
Annual demand
TRANSPORTATION DATA: TARGET
Origins
1
2
3
4
5
.
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M
Destinations
1
2
3
X
4
5.......N
Average cost/cwt
GEOGRAPHIC AGGREGATION
1-DIGIT ZIP ZONE
5
0
9
8
6
7
1
4
2
3
TRADITIONAL CAPACITY LIMITS
Capacity
Limit
UNIT
VARIABLE
COST
VOLUME
“ELASTIC” CAPACITY LIMITS
Capacity
Limit
UNIT
VARIABLE
COST
}
Penalty
VOLUME
Integrated Logistics
Case Study
ADF, Inc.
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Manufacturer of consumer goods
Founded in 1927
Sales in 1980: $460mil
12 major categories of product
2 production technologies
11,000 customers
100,000 orders per year
98% fill rate with 7 day order cycle
5 plants and 17 distribution centers
Historical Situation - 1930
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Plant
Distribution center
Market area
$
Transportation
to Customers
ADF DISTRIBUTION
COST RELATIONSHIPS
1930 (est.)
Transportation
to Warehouse
Warehousing
Inventory
Carrying Costs
HISTORICAL SITUATION - 1940
P1
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Plant
Distribution center
Market area
P1
HISTORICAL SITUATION - 1950
P1,
P2
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Plant
Distribution center
Market area
P1
P2
HISTORICAL SITUATION - 1960
P1,
P2
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Plant
Distribution center
Market area
Local overflow warehouse
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
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P1
P2
HISTORICAL SITUATION - 1970
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P1,
P2
P2
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Plant
Distribution center
Market area
 P1
 P2
 P1
AT TIME OF STUDY
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P1,
P2
 P1
 P2
 P1
 P2
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Plant
Distribution center
Market area
CURRENT ADF DISTRIBUTION COSTS
$
Transportation
to Customers
Transportation
to Warehouse
Inventory
Carrying Costs
Warehousing
PD/Percent
of COGS
10
8
_
11.4%

Actual
8.2%
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6.5%
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4
_ DISTRIBUTION COSTS GROWING
FASTER THAN MANUFACTURING COSTS
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2
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1960
1970
_
6
study
DISTRIBUTION COSTS
GROWING FASTER THAN SALES $463 MM
P.D. Costs
Percent of Sales
1970 - 5.8%
study - 8.0%
Distribution
Sales
$138 MM
$8 MM
1970
$37 MM
study
INVENTORY TURNOVER DECLINING
Finished Goods Inventory
Cost of Goods Sold
$324 MM
Inventory Turns
1970 - 7.5
study - 6.0
$97 MM
$54 MM
$13 MM
1970
study
MANAGEMENT’S RESPONSES HAVE BEEN
INCREMENTAL AND SUBOPTIMAL
Impact on functional area
Manufacturing
costs
Arbitrary
inventory cuts
Additional
warehouses
Mode mix
changes
Plant warehouse
space usurped
Transportation
costs
Warehousing
costs
Inventory
costs
Customer
service/sales
MANAGEMENT OBJECTIVE
Fundamental question asked
by management . . .
What production-distribution network
will yield greatest return on assets,
given all trade-offs in the system?
Specific Issues
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What are the appropriate customer service goals to pursue?
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How should inventory be stratified and positioned in the various
levels of the production - distribution system?
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How many distribution centers should there be, where should they
be, and what service areas should be assigned to each?
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Should new plant locations be opened and should the production
mix among plants be changed?
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Which plants should provide which products to each warehouse
and what mix of transportation modes should be used?
RECONFIGURED SYSTEM
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
P1, P2
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
P1
P2
 P1
P1, P2
 P2

Plant
Dist. center
Change in:
Plants
Distribution Centers
5
17
6
9
Distribution Center Replenishment Flows
22
6
Financial Results
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Actual
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Reduction in Distribution Costs of 20%
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Fewer DCs
Less Plant to DC freight
Less inventory
Increase in ROA of 8% over an already favorable 12.5%
Expected
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Improvement in customer service/satisfaction
More streamlined network
Improved inventory deployment
Outcome of Specific Contingency Analyses
If
• TL increases disproportionately
vs. LTL
Then
• West Coast plant more
advantageous
• LTL increases
disproportionately vs. TL
• 3 more warehouses feasible
• Service level (order cycle time)
relaxed
• 1 less warehouse feasible
• Unit production cost estimates
at new plant low by >10%
• Logistics benefits of new
plant negated
• Cost of money under 10%
• 4 additional warehouses
feasible
Network Evaluation Process
Manufacturing
technology
Raw material
availability
Corporate
policies/
strategies
Service
goals
Marketing
goals
Future
transportation
costs
Financial
goals
Plan & Launch
Project
Generate
Baseline
Optimization
of existing
network
Alternate
scenario
definition
Alternate
scenario
optimization
analysis
Management
Analysis
Integrated Logistics
Summary